Soo‐Youn Ham

541 citations
36 papers · 345 · h-index 9

Impact in

Papers in

    • Lung Cancer Diagnosis and Treatment 5
    • Chronic Obstructive Pulmonary Disease (COPD) Research 5
    • Digital Radiography and Breast Imaging 3
    • Lung Cancer Treatments and Mutations 3
    • Radiomics and Machine Learning in Medical Imaging 5
    • Medical Imaging Techniques and Applications 4
    • COVID-19 diagnosis using AI 2

Soo‐Youn Ham

31 papers receiving 334 citations

Peers

Soo‐Youn Ham
Comparison fields: 5 of 73
  • Radiology, Nuclear Medicine and Imaging 167
  • Pulmonary and Respiratory Medicine 123
  • Cancer Research 50
  • Artificial Intelligence 105
  • Oncology 54
Replace Fatma Tokat with:
Fatma Tokat Türkiye
Tiebao Meng China
Ying Su China
Bingjie Zheng China
Romuald Ferré Canada
Rebecca Batiste United States
Haohua Teng China
Toshiyuki Ishiba Japan
Afsaneh Alikhassi Iran
Jeon‐Hor Chen Taiwan
Soo‐Youn Ham relative to Fatma Tokat Türkiye Fatma Tokat's profile →
Citations per field
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Citations per year

Countries citing papers authored by Soo‐Youn Ham

Since Specialization
Citations

This map shows the geographic impact of Soo‐Youn Ham's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Soo‐Youn Ham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soo‐Youn Ham more than expected).

Fields of papers citing papers by Soo‐Youn Ham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soo‐Youn Ham. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Soo‐Youn Ham. The network helps show where Soo‐Youn Ham may publish in the future.

Co-authors

The 25 scholars most cited alongside Soo‐Youn Ham, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Soo‐Youn Ham Line = papers co-authored together Soo‐Youn Ham links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201894
2 201847
3 201929
4 201922
5 201418
6 202012
7 201911
8 202210
9 20208
10 20198
11 20188
12 20247
13 20206
14 20206
15 20076
16 20186
17 20235
18 20225
19 20085
20 20085

About Soo‐Youn Ham

Soo‐Youn Ham is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Epidemiology, Oncology and Surgery, having authored 36 papers that have together received 345 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (5 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Imaging Techniques and Applications (4 papers), Digital Radiography and Breast Imaging (3 papers), Liver Disease Diagnosis and Treatment (3 papers), Lung Cancer Treatments and Mutations (3 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (167 citations), Pulmonary and Respiratory Medicine (123 citations), Cancer Research (50 citations), Artificial Intelligence (105 citations) and Oncology (54 citations). Soo‐Youn Ham has collaborated with scholars based in South Korea, United Kingdom and Japan. Frequent co-authors include Hwejin Jung, Bumsoo Kim, Junhyun Lee, Jaewoo Kang, Shin Ho Kook, Eun Young Kim, Inyoung Youn, Chan Heun Park, Yoon Jung Choi and Min Ja Kim. Their work appears in journals such as Medicine, PLoS ONE, Korean Journal of Radiology, British Journal of Radiology and Biochemical and Biophysical Research Communications.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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